| 1. |
- Bekiroglu, Yasemin, et al.
(författare)
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Integrating Grasp Planning with Online Stability Assessment using Tactile Sensing
- 2011
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Ingår i: IEEE International Conference on Robotics and Automation. - : IEEE conference proceedings. - 1050-4729. - 9781612843865 ; , s. 4750-4755
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Konferensbidrag (refereegranskat)abstract
- This paper presents an integration of grasp planning and online grasp stability assessment based on tactile data. We show how the uncertainty in grasp execution posterior to grasp planning can be dealt with using tactile sensing and machine learning techniques. The majority of the state-of-the-art grasp planners demonstrate impressive results in simulation. However, these results are mostly based on perfect scene/object knowledge allowing for analytical measures to be employed. It is questionable how well these measures can be used in realistic scenarios where the information about the object and robot hand may be incomplete and/or uncertain. Thus, tactile and force-torque sensory information is necessary for successful online grasp stability assessment. We show how a grasp planner can be integrated with a probabilistic technique for grasp stability assessment in order to improve the hypotheses about suitable grasps on different types of objects. Experimental evaluation with a three-fingered robot hand equipped with tactile array sensors shows the feasibility and strength of the integrated approach.
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| 2. |
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| 3. |
- Ek, Carl Henrik, et al.
(författare)
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Task Modeling in Imitation Learning using Latent Variable Models
- 2010
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Ingår i: 2010 10th IEEE-RAS International Conference on Humanoid Robots, Humanoids 2010. ; , s. 458-553
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Konferensbidrag (refereegranskat)abstract
- An important challenge in robotic research is learning and reasoning about different manipulation tasks from scene observations. In this paper we present a probabilistic model capable of modeling several different types of input sources within the same model. Our model is capable to infer the task using only partial observations. Further, our framework allows the robot, given partial knowledge of the scene, to reason about what information streams to acquire in order to disambiguate the state-space the most. We present results for task classification within and also reason about different features discriminative power for different classes of tasks.
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| 4. |
- Huebner, Kai
(författare)
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BADGr-A toolbox for box-based approximation, decomposition and GRasping
- 2012
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Ingår i: Robotics and Autonomous Systems. - : Elsevier BV. - 0921-8890 .- 1872-793X. ; 60:3, s. 367-376
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Tidskriftsartikel (refereegranskat)abstract
- In this paper, we conclude our work on shape approximation by box primitives for the goal of simple and efficient grasping. As a main product of our research, we present the BADGr toolbox for Box-based Approximation, Decomposition and Grasping of objects. The contributions of the work presented here are twofold: in terms of shape approximation, we provide an algorithm for creating a 3D box primitive representation to identify object parts from 3D point clouds. We motivate and evaluate this choice particularly towards the task of grasping. As a contribution in the field of grasping, we further provide a grasp hypothesis generation framework that utilizes the chosen box presentation in a flexible manner.
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| 5. |
- Lavoué, G., et al.
(författare)
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SHREC'12 Track : 3D mesh segmentation
- 2012
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Ingår i: Eurographics Workshop on 3D Object Retrieval, EG 3DOR. - 9783905674361 ; , s. 93-99
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Konferensbidrag (refereegranskat)abstract
- 3D mesh segmentation is a fundamental process in many applications such as shape retrieval, compression, deformation, etc. The objective of this track is to evaluate the performance of recent segmentation methods using a ground-truth corpus and an accurate similarity metric. The ground-truth corpus is composed of 28 watertight models, grouped in five classes (animal, furniture, hand, human and bust) and each associated with 4 ground-truth segmentations done by human subjects. 3 research groups have participated to this track, the accuracy of their segmentation algorithms have been evaluated and compared with 4 other state-of-the-art methods.
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